Informing BC Stakeholders

You are here

Publications Library

  • Source Publication: Atmospheric Chemistry and Physics, 18, 10133-10156, doi:10.5194/acp-18-10133-2018. Authors: Ji, D., S. Fang, C.L. Curry, H. Kashimura, S. Watanabe, J.N.S. Cole, A. Lenton, H. Muri, B. Kravitz and J.C. Moore Publication Date: Jul 2018

    We examine extreme temperature and precipitation under two potential geoengineering methods forming part of the Geoengineering Model Intercomparison Project (GeoMIP). The solar dimming experiment G1 is designed to completely offset the global mean radiative forcing due to a CO2-quadrupling experiment (abrupt4 × CO2), while in GeoMIP experiment G4, the radiative forcing due to the representative concentration pathway 4.5 (RCP4.5) scenario is partly offset by a simulated layer of aerosols in the stratosphere. Both G1 and G4 geoengineering simulations lead to lower minimum temperatures (TNn) at higher latitudes and on land, primarily through feedback effects involving high-latitude processes such as snow cover, sea ice and soil moisture. There is larger cooling of TNn and maximum temperatures (TXx) over land compared with oceans, and the land–sea cooling contrast is larger for TXx than TNn. Maximum 5-day precipitation (Rx5day) increases over subtropical oceans, whereas warm spells (WSDI) decrease markedly in the tropics, and the number of consecutive dry days (CDDs) decreases in most deserts. The precipitation during the tropical cyclone (hurricane) seasons becomes less intense, whilst the remainder of the year becomes wetter. Stratospheric aerosol injection is more effective than solar dimming in moderating extreme precipitation (and flooding). Despite the magnitude of the radiative forcing applied in G1 being ∼ 7.7 times larger than in G4 and despite differences in the aerosol chemistry and transport schemes amongst the models, the two types of geoengineering show similar spatial patterns in normalized differences in extreme temperatures changes. Large differences mainly occur at northern high latitudes, where stratospheric aerosol injection more effectively reduces TNn and TXx. While the pattern of normalized differences in extreme precipitation is more complex than that of extreme temperatures, generally stratospheric aerosol injection is more effective in reducing tropical Rx5day, while solar dimming is more effective over extra-tropical regions.

  • Authors: Anslow, F.S., S. Tam, J. Lussier Publication Date: Jun 2018

    Presented by Faron Anslow at the Canadian Meteorological and Oceanographic Society’s 52nd Congress.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Jun 2018

    The June 2018 PCIC Update includes the following stories: New on the Data Portal from the Hydrologic Impacts Theme: Gridded Meteorological Datasets, Updated Guidance for the Engineering Community, Climate Data for the Northwest Territories and Yukon, Agricultural Data Network Analysis, Renewed Climate Related Monitoring Program Agreement, Regional Assessment for Northeastern BC, Fraser Valley Extremes, New Projects, Staff Profile on Stephen Sobie and the Pacific Climate Seminar Series, as well as staff changes and publications.

  • Source Publication: Stochastic Environmental Research and Risk Assessment</em>, <b>32</b>, 10, 2821–2836, doi:/10.1007/s00477-018-1564-7. Authors: Ouali, D. and A.J. Cannon Publication Date: May 2018

    Intensity–duration–frequency (IDF) curves of extreme rainfall are used extensively in infrastructure design and water resources management. In this study, a novel regional framework based on quantile regression (QR) is used to estimate rainfall IDF curves at ungauged locations. Unlike standard regional approaches, such as index-storm and at-site ordinary least-squares regression, which are dependent on parametric distributional assumptions, the non-parametric QR approach directly estimates rainfall quantiles as a function of physiographic characteristics. Linear and nonlinear methods are evaluated for both the regional delineation and IDF curve estimation steps. Specifically, delineation by canonical correlation analysis (CCA) and nonlinear CCA (NLCCA) is combined, in turn, with linear QR and nonlinear QR estimation in a regional modelling framework. An exhaustive comparative study is conducted between standard regional methods and the proposed QR framework at sites across Canada. Overall, the fully nonlinear QR framework, which uses NLCCA for delineation and nonlinear QR for estimation of IDF curves at ungauged sites, leads to the best results.

  • Source Publication: Climate Dynamics, doi:10.1007/s00382-018-4145-z. Authors: Wan, H., X. Zhang and F. Zwiers Publication Date: May 2018

    Canada has experienced some of the most rapid warming on Earth over the past few decades with a warming rate about twice that of the global mean temperature since 1948. Long-term warming is observed in Canada’s annual, winter and summer mean temperatures, and in the annual coldest and hottest daytime and nighttime temperatures. The causes of these changes are assessed by comparing observed changes with climate model simulated responses to anthropogenic and natural (solar and volcanic) external forcings. Most of the observed warming of 1.7 °C increase in annual mean temperature during 1948–2012 [90% confidence interval (1.1°, 2.2 °C)] can only be explained by external forcing on the climate system, with anthropogenic influence being the dominant factor. It is estimated that anthropogenic forcing has contributed 1.0 °C (0.6°, 1.5 °C) and natural external forcing has contributed 0.2 °C (0.1°, 0.3 °C) to the observed warming. Up to 0.5 °C of the observed warming trend may be associated with low frequency variability of the climate such as that represented by the Pacific decadal oscillation (PDO) and North Atlantic oscillation (NAO). Overall, the influence of both anthropogenic and natural external forcing is clearly evident in Canada-wide mean and extreme temperatures, and can also be detected regionally over much of the country.

  • Source Publication: Comptes Rendus Geoscience, 350, 4, 41-153, Authors: Dayon G., J. Boé, É. Martin and J. Gailhard Publication Date: May 2018

    This study deals with the evolution of the hydrological cycle over France during the 21st century. A large multi-member, multi-scenario, and multi-model ensemble of climate projections is downscaled with a new statistical method to drive a physically-based hydrological model with recent improvements. For a business-as-usual scenario, annual precipitation changes generally remain small, except over southern France, where decreases close to 20% are projected. Annual streamflows roughly decrease by 10% (±20%) on the Seine, by 20% (±20%) on the Loire, by 20% (±15%) on the Rhone and by 40% (±15%) on the Garonne. Attenuation measures, as implied by the other scenarios analyzed, lead to less severe changes. However, even with a scenario generally compatible with a limitation of global warming to two degrees, some notable impacts may still occur, with for example a decrease in summer river flows close to 25% for the Garonne.

  • Source Publication: Climatic Change, 148, 1-2, 249-263, doi: 10.1007/s10584-018-2199-x Authors: Zhang, X., G. Li, A. Cannon, T. Murdock, S. Sobie, F.W. Zwiers, K. Anderson and B. Qian Publication Date: May 2018

    This study evaluates regional-scale projections of climate indices that are relevant to climate change impacts in Canada. We consider indices of relevance to different sectors including those that describe heat conditions for different crop types, temperature threshold exceedances relevant for human beings and ecological ecosystems such as the number of days temperatures are above certain thresholds, utility relevant indices that indicate levels of energy demand for cooling or heating, and indices that represent precipitation conditions. Results are based on an ensemble of high-resolution statistically downscaled climate change projections from 24 global climate models (GCMs) under the RCP2.6, RCP4.5, and RCP8.5 emissions scenarios. The statistical downscaling approach includes a bias-correction procedure, resulting in more realistic indices than those computed from the original GCM data. We find that the level of projected changes in the indices scales well with the projected increase in the global mean temperature and is insensitive to the emission scenarios. At the global warming level about 2.1 °C above pre-industrial (corresponding to the multi-model ensemble mean for 2031–2050 under the RCP8.5 scenario), there is almost complete model agreement on the sign of projected changes in temperature indices for every region in Canada. This includes projected increases in extreme high temperatures and cooling demand, growing season length, and decrease in heating demand. Models project much larger changes in temperature indices at the higher 4.5 °C global warming level (corresponding to 2081–2100 under the RCP8.5 scenario). Models also project an increase in total precipitation, in the frequency and intensity of precipitation, and in extreme precipitation. Uncertainty is high in precipitation projections, with the result that models do not fully agree on the sign of changes in most regions even at the 4.5 °C global warming level.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: May 2018

    In this Science Brief we consider two aspects of climate change that are of direct interest to Canadians—the warming of the Canadian climate and changes in high water events that affect our coasts. Two articles recently published in the peer reviewed literature discuss the contribution of waves to coastal sea level rise and the roles of human and natural influences in Canada's warming climate.

    Publishing in Nature Climate Change, Melet et al. (2018) study the effect of atmospheric surges, tides and waves on total water level rise at the coast. Using a mixture of model output and observations from the 1993-2015 period, they find that the size of wave contributions from several processes varies regionally. These processes can strengthen, offset or, as is the case for locations on the west coast of North America, entirely dominate sea level rise due to thermal expansion and land ice melting. In their article in Climate Dynamics,

    Wan, Zhang and Zwiers (2018) examine the roles that human and natural influences have played in Canada's warming climate from 1948 to 2012, both nationally and regionally. Comparing observations to climate model simulations, they find that about 1.0°C of the 1.7°C warming that Canada experienced over that period can be attributed to anthropogenic influences, while natural external influences (the sun and volcanic eruptions) contributed only about 0.2°C. For the region comprised of British Columbia and Yukon, which has experienced a 1.6°C warming, they find that about 0.8°C is attributable to anthropogenic influences and about 0.2°C to natural influences. They also find that, in most cases, anthropogenic influences can be detected in changes to the annual hottest and coldest daytime and nighttime temperatures for Canada as a whole and at the regional level. Natural influences can generally only be detected in changes to the coldest winter nighttime and daytime temperatures, both nationally and regionally.

  • Authors: Wilson, T. and Eco-Logical Resolutions Publication Date: Apr 2018

    The Fraser Valley Climate Adaptive Drainage Management Forum project was initiated to generate and share the best available precipitation projections for the Fraser Valley; research collaborative climate adaptive drainage management strategies adopted in comparable settings; and host a Forum between producers, local government and agency staff, researchers and agricultural association representatives to deliberate preferred drainage management strategies to address local runoff and drainage challenges.

  • Source Publication: Hydrology and Earth System Sciences, doi:10.5194/hess-2017-531 Authors: Curry, C.L. and F.W. Zwiers Publication Date: Apr 2018

    The Fraser River Basin (FRB) of British Columbia is one of the largest and most important watersheds in western North America, and home to a rich diversity of biological species and economic assets that depend implicitly upon its extensive riverine habitats. The hydrology of the FRB is dominated by snow accumulation and melt processes, leading to a prominent annual peak streamflow invariably occurring in May–July. Nevertheless, while annual peak daily streamflow (APF) during the spring freshet in the FRB is historically well correlated with basin-averaged, 1 April snow water equivalent (SWE), there are numerous occurrences of anomalously large APF in below- or near-normal SWE years, some of which have resulted in damaging floods in the region. An imperfect understanding of which other climatic factors contribute to these anomalously large APFs hinders robust projections of their magnitude and frequency. We employ the Variable Infiltration Capacity (VIC) process-based hydrological model driven by gridded observations to investigate the key controlling factors of anomalous APF events in the FRB and four of its subbasins that contribute nearly 70 % of the annual flow at Fraser-Hope. The relative influence of a set of predictors characterizing the interannual variability of rainfall, snowfall, snowpack (characterized by the annual maximum value, SWEmax), soil moisture and temperature on simulated APF at Hope (the main outlet of the FRB) and at the subbasin outlets is examined within a regression framework. The influence of large-scale climate modes of variability (the Pacific Decadal Oscillation (PDO) and the El Niño–Southern Oscillation – ENSO) on APF magnitude is also assessed, and placed in context with these more localized controls. The results indicate that next to SWEmax (univariate Spearman correlation with APF of ρˆ = 0.64; 0.70 (observations; VIC simulation)), the snowmelt rate (ρˆ = 0.43 in VIC), the ENSO and PDO indices (ρˆ = −0.40; −0.41) and (ρˆ = −0.35; −0.38), respectively, and rate of warming subsequent to the date of SWEmax (ρˆ = 0.26; 0.38), are the most influential predictors of APF magnitude in the FRB and its subbasins. The identification of these controls on annual peak flows in the region may be of use in understanding seas

  • Authors: M. Ek, T. Murdock, S. Sobie, B. Cavka, B. Coughlin and R. Wells Publication Date: Apr 2018

    Since local weather and climate greatly affect the construction and performance of buildings, reliable meteorological
    data is essential when simulating building performance. It is well understood that climate change will affect future
    weather and there is a growing interest in generating future weather files to support climate resilient building design.
    Weather files that account for climate change have not been widely used for the lower mainland region of British
    Columbia. In this study, hourly weather files for future climate conditions in Vancouver are created for three time periods
    using a “morphing” methodology. Morphing uses results from global climate models to adjust observed weather data
    at a specific location. In this study, daily data from climate simulations for the RCP8.5 emission scenario have been
    used. The weather variables that have been adjusted are dry-bulb temperature, relative humidity, solar radiation, cloud
    cover, wind speed and atmospheric pressure. The impact of climate change on the energy performance of a multi-unit
    residential building located on the University of BC campus is analyzed using the energy modelling software
    EnergyPlus. The simulation results indicate that the changing climate in Vancouver, following RCP8.5, would have a
    considerable effect on building energy performance and energy demand due to decrease in space heating and increase
    in cooling requirements.

  • Source Publication: Journal of Hydrometeorology, doi: 10.1175/JHM-D-17-0110.1 Authors: Ben Alaya, M.A., F.W. Zwiers and X. Zhang Publication Date: Apr 2018

    Probable maximum precipitation (PMP) is the key parameter used to estimate the probable maximum flood (PMF), both of which are important for dam safety and civil engineering purposes. The usual operational procedure for obtaining PMP values, which is based on a moisture maximization approach, produces a single PMP value without an estimate of its uncertainty. We therefore propose a probabilistic framework based on a bivariate extreme value distribution to aid in the interpretation of these PMP values. This 1) allows us to evaluate estimates from the operational procedure relative to an estimate of a plausible distribution of PMP values, 2) enables an evaluation of the uncertainty of these values, and 3) provides clarification of the impact of the assumption that a PMP event occurs under conditions of maximum moisture availability. Results based on a 50-yr Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) simulation over North America reveal that operational PMP estimates are highly uncertain and suggest that the assumption that PMP events have maximum moisture availability may not be valid. Specifically, in the climate simulated by CanRCM4, the operational approach applied to 50-yr data records produces a value that is similar to the value that is obtained in our approach when assuming complete dependence between extreme precipitation efficiency and extreme precipitable water. In contrast, our results suggest weaker than complete dependence. Estimates from the operational approach are 15% larger on average over North America than those obtained when accounting for the dependence between precipitation efficiency and precipitable water extremes realistically. A difference of this magnitude may have serious implications in engineering design.

  • Source Publication: Earth's Future, 6, doi: 10.1002/2018EF000813 Authors: Kharin, V.V., G.M. Flato, X. Zhang, N.P. Gillett, F.W. Zwiers and K. Anderson Publication Date: Apr 2018

    Parties to the United Nations Framework Convention on Climate Change have agreed to hold the “increase in global average temperature to well below 2°C above preindustrial levels and to pursue efforts to limit the temperature increase to 1.5°C.” Comparison of the costs and benefits for different warming limits requires an understanding of how risks vary between warming limits. As changes in risk are often associated with changes in exposure due to projected changes in local or regional climate extremes, we analyze differences in the risks of extreme daily temperatures and extreme daily precipitation amounts under different warming limits. We show that global warming of 2°C would result in substantially larger changes in the probabilities of the extreme events than global warming of 1.5°C. For example, over the global land area, the probability of a warm extreme that occurs once every 20 years on average in the current climate is projected to increase 130% and 340% at the 1.5°C and 2.0°C warming levels, respectively (median values). Moreover, the relative changes in probability are larger for rarer, more extreme events, implying that risk assessments need to carefully consider the extreme event thresholds at which vulnerabilities occur.

  • Authors: Anslow, F.S. Publication Date: Mar 2018

    Presented by Faron Anslow at the State of the Pacific Ocean meeting.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Mar 2018

    Two recent articles in the journal Climatic Change examine some of the effects that climate change may have on agriculture in the Pacific Northwest.

    Focusing on specialty fruit production, Houston et al. (2018) find that overall warmer conditions and reduced water availability may reduce net returns on crops due to increasing farming costs, affecting yields and altering product quality. They suggest that management strategies currently employed in marginal production areas that moderate temperatures and offset mismatches between the needs of the plant at various growth stages and seasonal weather conditions may be useful adaptation strategies.

    Neibergs and colleagues (2018) review the impacts of climate change on beef cattle production. They find that changes to seasonal temperature and precipitation may affect the availability of the plants on which cattle forage. This in turn could affect the number of cattle that an area can support, and the dates at which cattle are "turned-out" to pasture and taken in from pasture.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Mar 2018

    The March 2018 PCIC Update includes the following stories: 2017 in Climatological Context, Applying the Updated VIC Model to New Regions, Engagement with First Nations Communities and Engineers, New Projects, Staff Profile on Dr. Faron Anslow and the Pacific Climate Seminar Series, as well as staff changes and publications.

  • Source Publication: Agricultural and Forest Meteorology, 250–251, 226-242 doi:10.1016/j.agrformet.2017.12.253 Authors: Sgubin, G., D. Swingedouw, G. Dayon, I.G. de Cortázar-Atauri, N. Ollat, C. Pagé and , C. van Leeuwen Publication Date: Mar 2018

    Tardive frosts, i.e. frost events occurring after grapevine budburst, are a significant risk for viticultural practices, which have recently caused substantial yield losses over different winegrowing regions of France, e.g. in 2016 and 2017. So far, it is unclear whether the frequency of late frosts events is destined to increase or decrease under future climatic conditions. Here, we assess the risk of tardive frosts for the French vineyards throughout the 21st century by analyzing temperature projections from eight climate models and their statistical regional downscaling. Our approach consists in comparing the statistical occurrences of the last frost (day of the year) and the characteristic budburst date for nine grapevine varieties as simulated by three different phenological models. Climate models qualitatively agree in projecting a gradual increase in temperature all over the France, which generally produces both an earlier characteristic last frost day and an earlier characteristic budburst date. However, the latter notably depends on the specific phenological model, implying a large uncertainty in assessing the risk exposure. Overall, we identified Alsace, Burgundy and Champagne as the most vulnerable regions, where the probability of tardive frost is projected to significantly increase throughout the 21st century for two out of three phenological models. The third phenological model produces opposite results, but the comparison between simulated budburst dates and observed records over the last 60 years suggests its lower reliability. Nevertheless, for a more trustworthy risk assessment, the validity of the budburst models should be accurately tested also for warmer climate conditions, in order to narrow down the associated large uncertainty.

  • Source Publication: The Journal of Open Source Software. 3, 22, 360, doi:10.21105/joss.00360 Authors: Hiebert, J., A. Cannon, A. Schoeneberg, S. Sobie and T. Murdock Publication Date: Feb 2018

    The ClimDown R package publishes the routines and techniques of the Pacific Climate Impacts Consortium (PCIC) for downscaling coarse scale Global Climate Models (GCMs) to fine scale spatial resolution. PCIC’s overall downscaling algorithm is named Bias-corrected constructed analogues with quantile mapping reordering (BCCAQ) (Cannon, Sobie, and Murdock 2015; Werner and Cannon 2016). BCCAQ is a hybrid downscaling method that combines outputs from Constructed Analogues (CA) (Maurer et al. 2010) and quantile mapping at the fine-scale resolution. First, the CA and Climate Imprint (CI) (Hunter and Meentemeyer 2005) plus quantile delta mapping (QDM) (Cannon, Sobie, and Murdock 2015) algorithms are run independently. BCCAQ then combines outputs from the two by taking the daily QDM outputs at each fine-scale grid point and reordering them within a given month according to the daily CA ranks, i.e., using a form of Empirical Copula Coupling (Schefzik, Thorarinsdottir, and Gneiting 2013). The package exports high-level wrapper functions that perform each of three downscaling steps: CI, CA, and QDM, as well as one wrapper that runs the entire BCCAQ pipeline.

  • Authors: The Pacific Climate Impacts Consortium Publication Date: Feb 2018

    Three recent journal articles examine the rate of sea level rise and the ability of models to accurately simulate sea level rise at a global and regional scale.

    Publishing in Geophysical Research Letters, Yi et al. (2017) examine the rate at which sea level rise is accelerating and find that the rate of acceleration over the 2005-2015 period is three times faster than it was over the 1993-2014 period and an order of magnitude larger than the acceleration over the 1920-2011 period. They also identify three primary contributors to this acceleration: the thermal expansion of sea water, reduced storage of water on land and the melting of ice on land.

    In a pair of articles published in the Journal of Climate, Slangen et al. (2017) and Meyssignac et al. (2017) analyze the of climate models to simulate both global and regional sea level rise. They find that simulations can only explain about half (50% ± 30%) of the observed sea level rise. After bias corrections are included for the Greenland ice sheet and the possibility that ice sheets and the deep ocean were not in equilibrium with the 20th Century climate, the models explain about three-quarters (75% ± 38%) of the observed 20th Century sea level rise and all (105% ± 35%) of the observed sea level rise over the period from 1993-1997 to 2011-2015 period. Regionally, climate models underestimate the amount of sea level rise that occured, but do show reasonable agreement for interannual and multidecadal variability. When the same bias corrections are applied, the models come into closer agreement with observations. In addition, they find that the spatial variability in regional sea level rise is largely due to the thermal expansion of sea water and ongoing isostatic adjustment resulting from the end of the last glacial period.

  • Source Publication: International Journal of Climatology, 38, 2, 1041-1059, doi:10.1002/joc.5235 Authors: Pingree-Shippee, K., F.W. Zwiers and D. Atkinson Publication Date: Feb 2018

    Extratropical cyclones often produce extreme and hazardous weather conditions, such as high winds, heavy precipitation, blizzard conditions, and flooding, all of which have detrimental environmental/physical and socio‐economic impacts. Furthermore, storm interaction with the ocean produces additional hazards, with major local impacts, including inundation and coastal erosion. The North American west coast is influenced by the North Pacific storm track and by ‘atmospheric river’ events while the east coast is particularly influenced by winter storms that track along two favoured routes: the St. Lawrence Valley and the Eastern Seaboard. Reanalysis provides an invaluable tool for studying the characteristics of storm events that are identified as causing the most severe impacts. However, reanalysis products differ substantially in spatial resolution, model physics, assimilation approach, and the data that are assimilated. This study evaluates the representation of storm activity along the mid‐latitude North American coastlines by six global reanalyses: NCEP‐1, NCEP‐2, ERA‐Interim, Modern‐Era Retrospective analysis for Research and Applications (MERRA), Climate Forecast System Reanalysis (CFSR), and Twentieth Century Reanalysis Version 2 (20CR). Storm activity representation is evaluated at annual and seasonal timescales (JFM, AMJ, JAS, OND, and ‘extended winter’ ONDFM) during the 1979–2010 time period through comparison with selected meteorological stations using single‐point surface pressure‐based proxies of extratropical storm activity. Stations are selected on the basis of record length, reporting frequency, coastal proximity, and relatively uniform spatial distribution. Comparisons are made using data extracted from the reanalysis grid box centre that is closest to each selected station. All reanalyses are found to successfully represent most aspects of mid‐latitude North American coastal strong storm activity, annually and seasonally, along both coasts. Nevertheless, ERA‐Interim, MERRA, and CFSR provide the better representations of mid‐latitude North American coastal strong storm activity, with ERA‐Interim performing best overall.